Search results for: patient dose optimization

Authors: Julius M. Ndambuki, Gislar E. Kifanyi, Samuel N. Odai, Charles Gyamfi

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Conjunctive management of surface and groundwater resources is a challenging task due to the spatial and temporal variability nature of hydrology as well as hydrogeology of the water storage systems. Surface water-groundwater hydrogeology is highly uncertain; thus it is imperative that this uncertainty is explicitly accounted for, when managing water resources. Various methodologies have been developed and applied by researchers in an attempt to account for the uncertainty. For example, simulation-optimization models are often used for conjunctive water resources management. However, direct application of such an approach in which all realizations are considered at each iteration of the optimization process leads to a very expensive optimization in terms of computational time, particularly when the number of realizations is large. The aim of this paper, therefore, is to introduce and apply an efficient approach referred to as Retrospective Optimization Approximation (ROA) that can be used for optimizing conjunctive use of surface water and groundwater over a multiple hydrogeological model simulations. This work is based on stochastic simulation-optimization framework using a recently emerged technique of sample average approximation (SAA) which is a sampling based method implemented within the Retrospective Optimization Approximation (ROA) approach. The ROA approach solves and evaluates a sequence of generated optimization sub-problems in an increasing number of realizations (sample size). Response matrix technique was used for linking simulation model with optimization procedure. The k-means clustering sampling technique was used to map the realizations. The methodology is demonstrated through the application to a hypothetical example. In the example, the optimization sub-problems generated were solved and analysed using “Active-Set” core optimizer implemented under MATLAB 2014a environment. Through k-means clustering sampling technique, the ROA – Active Set procedure was able to arrive at a (nearly) converged maximum expected total optimal conjunctive water use withdrawal rate within a relatively few number of iterations (6 to 7 iterations). Results indicate that the ROA approach is a promising technique for optimizing conjunctive water use of surface water and groundwater withdrawal rates under hydrogeological uncertainty.

Keywords: conjunctive water management, retrospective optimization approximation approach, sample average approximation, uncertainty

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Authors: Tomoaki Hashimoto

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In recent decades, probabilistic constrained optimal control problems have attracted much attention in many research field. Although probabilistic constraints are generally intractable in an optimization problem, several tractable methods haven been proposed to handle probabilistic constraints. In most methods, probabilistic constraints are reduced to deterministic constraints that are tractable in an optimization problem. However, there is a gap between the transformed deterministic constraints in case of known and unknown probability distribution. This paper examines the conservativeness of probabilistic constrained optimization method with the unknown probability distribution. The objective of this paper is to provide a quantitative assessment of the conservatism for tractable constraints in probabilistic constrained optimization with the unknown probability distribution.

Keywords: optimal control, stochastic systems, discrete time systems, probabilistic constraints

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Authors: Martha C. Orazulume, Jibril D. Jiya

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Flexible satellites are equipped with various appendages which vibrate under the influence of any excitation and make the attitude of the satellite to be unstable. Therefore, the system must be able to adjust to balance the effect of these appendages in order to point accurately and satisfactorily which is one of the most important problems in satellite design. Proportional Integral Derivative (PID) Controller is simple to design and computationally efficient to implement which is used to stabilize the effect of these flexible appendages. However, manual turning of the PID is time consuming, waste energy and money. Particle Swarm Optimization (PSO) is used to tune the parameters of PID Controller. Simulation results obtained show that PSO tuned PID Controller is able to re-orient the spacecraft attitude as well as dampen the effect of mechanical resonance and yields better performance when compared with manually tuned PID Controller.

Keywords: Attitude Control, Flexible Satellite, Particle Swarm Optimization, PID Controller and Optimization

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Authors: Adrian Hang Yue Siu, Matthew Holyland, Sharon Carey, Daniel Steffens, Nabila Ansari, Cherry E. Koh

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Introduction: Peritoneal malignancies are challenging cancers to manage. While cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS and HIPEC) may offer a cure, it’s considered radical and morbid. Pre-emptive identification of deconditioned patients for optimization may mitigate the risks of surgery. However, the difficulty lies in the scarcity of validated predictive tools to identify high-risk patients. In recent times, there has been growing interest in sarcopenia, which can occur as a result of malnutrition and malignancies. Therefore, the purpose of this study was to assess the utility of sarcopenia in predicting post-operative outcomes. Methods: A single quaternary-center retrospective study of CRS and HIPEC patients between 2017-2020 was conducted to determine the association between pre-operative sarcopenia and post-operative outcomes. Lumbar CT images were analyzed using Slice-o-matic® to measure sarcopenia. Results : Cohort (n=94) analysis found that 40% had sarcopenia, with a majority being female (53.2%) and a mean age of 55 years. Sarcopenia was statistically associated with decreased weight compared to non-sarcopenia patients, 72.7kg vs. 82.2kg (p=0.014) and shorter overall survival, 1.4 years vs. 2.1 years (p=0.032). Post-operatively, patients with sarcopenia experienced more post-operative complications (p=0.001). Conclusion: Complex procedures often require optimization to prevent complications and improve survival. While patient biomarkers – BMI and weight – are used for optimization, this research advocates for the identification of sarcopenia status for pre-operative planning. Sarcopenia may be an indicator of advanced disease requiring further treatment and is an emerging area of research. Larger studies are required to confirm these findings and to assess the reversibility of sarcopenia after surgery.

Keywords: sarcopaenia, cytoreductive surgery, hyperthermic intraperitoneal chemotherapy, surgical oncology

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Authors: Ghada Esheba, Bayan Hafiz, Ashwaq Al-Qarni, Abdulelah AlMalki, Esraa Kaheel

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Hydatid disease is caused by genus Echinococcus, it is transmitted to human through sheep and cattle. People who lived in an endemic area should be suspected to have the disease. Pulmonary hydatid disease can be presented by respiratory manifestations as in our case. We report a case of child, 13 years old, who was presented by shortness of breath and non-productive cough 2 months ago. The patient had an attack of hemoptysis 3 months ago but there is no history of fever, other constitutional symptoms or any medical illness. The patient has had a close contact with a horse. On examination, the patient was oriented and vitally stable. Both side of chest were moving equally with decrease air entry on the left side of the chest. Cervical lymph node enlargement was also detected. The case was provisionally diagnosed as tuberculosis. The x-ray was normal, while CT scan showed two cysts in the left side. The patient was treated surgically with resection of both cysts without lobectomy. Broncho-alveolar lavage was done and together with plural effusion and both cysts were sent for histopathology. The patient received the following medication: albendazole 200MG/BID/Orally for 30 days and Cefuroxime 250MG/Q12H/Orally for 10 days.

Keywords: Echinococcus granulosus, hydatid disease, pediatrics, pulmonary hydatid cyst

Procedia PDF Downloads 273

Authors: Mitchell Gohnert

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This paper reviews some fundamental concepts of structural optimization, which is focused on the shape of the structure. Bending stresses produce high peak stresses at each face of the member, and therefore, substantially more material is required to resist bending. The shape of the structure has a profound effect on stress levels. Stress may be reduced dramatically by simply changing the shape to accommodate natural stress flow. The main objective of structural optimization is to direct the thrust line along the axis of the member. Optimal shapes include the catenary arch or dome, triangular shapes, and columns. If the natural flow of stress matches the shape of the structures, the most optimal shape is determined. Structures, however, must resist multiple load patterns. An optimal shape is still possible by ensuring that the thrust lines fall within the middle third of the member.

Keywords: optimization, natural structures, shells, catenary, domes, arches

Procedia PDF Downloads 43

Authors: Totok R. Biyanto, Arif T. Mardianto, M. Farid R. R., Luthfi Machmudi, kandi mulakasti

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The main objective of this research is optimizing the electrocoagulation process design as a post-treatment for biologically vinasse effluent process. The first principle model with three independent variables that affect the energy consumption of electrocoagulation process i.e. current density, electrode distance, and time of treatment process are chosen as optimized variables. The process condition parameters were determined with the value of pH, electrical conductivity, and temperature of vinasse about 6.5, 28.5 mS/cm, 52 oC, respectively. Aluminum was chosen as the electrode material of electrocoagulation process. Duelist algorithm was used as optimization technique due to its capability to reach a global optimum. The optimization results show that the optimal process can be reached in the conditions of current density of 2.9976 A/m2, electrode distance of 1.5 cm and electrolysis time of 119 min. The optimized energy consumption during process is 34.02 Wh.

Keywords: optimization, vinasse effluent, electrocoagulation, energy consumption

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Florin Leon, Silvia Curteanu

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The Bacterial Foraging Optimization (BFO) algorithm is inspired by the behavior of bacteria such as Escherichia coli or Myxococcus xanthus when searching for food, more precisely the chemotaxis behavior. Bacteria perceive chemical gradients in the environment, such as nutrients, and also other individual bacteria, and move toward or in the opposite direction to those signals. The application example considered as a case study consists in establishing the dependency between the reaction yield of hydrogels based on polyacrylamide and the working conditions such as time, temperature, monomer, initiator, crosslinking agent and inclusion polymer concentrations, as well as type of the polymer added. This process is modeled with a neural network which is included in an optimization procedure based on BFO. An experimental study of BFO parameters is performed. The results show that the algorithm is quite robust and can obtain good results for diverse combinations of parameter values.

Keywords: bacterial foraging, hydrogels, modeling and optimization, neural networks

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Authors: Daniel Kostrzewa, Henryk Josiński

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The expanded Invasive Weed Optimization algorithm (exIWO) is an optimization metaheuristic modelled on the original IWO version created by the researchers from the University of Tehran. The authors of the present paper have extended the exIWO algorithm introducing a set of both deterministic and non-deterministic strategies of individuals’ selection. The goal of the project was to evaluate the exIWO by testing its usefulness for solving some test instances of the traveling salesman problem (TSP) taken from the TSPLIB collection which allows comparing the experimental results with optimal values.

Keywords: expanded invasive weed optimization algorithm (exIWO), traveling salesman problem (TSP), heuristic approach, inversion operator

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Authors: Wajid Ali Khan

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Extensive experimentation and numerical investigation are performed to predict the machining-induced residual stresses in the end milling of AISI 1045 steel, and an optimization code has been developed using the particle swarm optimization technique. Experiments were conducted using a single factor at a time and design of experiments approach. Regression analysis was done, and a mathematical model of the cutting process was developed, thus predicting the machining-induced residual stress with reasonable accuracy. The mathematical model served as the objective function to be optimized using particle swarm optimization. The relationship between the different cutting parameters and the output variables, force, and residual stresses has been studied. The combined effect of the process parameters, speed, feed, and depth of cut was examined, and it is understood that 85% of the variation of these variables can be attributed to these machining parameters under research. A 3D finite element model is developed to predict the cutting forces and the machining-induced residual stresses in end milling operation. The results were validated experimentally and against the Johnson-cook model available in the literature.

Keywords: residual stresses, end milling, 1045 steel, optimization

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Authors: Yun-Tsuen Chen, Shih-Ting Huang, Pi-Fen Cheng, Yu-Ting Su, Joffrey Hsu, Hui-Zhu Chen

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Acute intestinal obstruction is one of the differentials of acute abdomen and requires timely alleviation of intestinal distention and abdominal pain to avoid perforation, intra-abdominal infection, and peritonitis. Investigation to identify the cause of obstruction will direct treatment planning and allow for more effective management. In this study, we present a 71-year-old female presenting with symptoms of acute intestinal obstruction for five days. After extensive history taking, physical exam, medical imaging, and pathology, the patient was diagnosed with colon cancer with lung metastasis and acute intestinal obstruction. The patient was placed on nil per os status with intravenous fluid support, intravenous antibiotics, and a decompression nasogastric tube was placed. The patient received decompression with colostomy creation surgery. After assessing the patient’s clinical condition and tumor staging, a multidisciplinary healthcare team created an individualized treatment plan, which included plans to prepare the patient for home self-care and maintain good mental health with regular monitoring in the clinic setting. This case demonstrates the importance of early diagnosis, effective treatment, and a multidisciplinary approach to the management of acute intestinal obstruction secondary to colon cancer.

Keywords: acute intestinal obstruction, colostomy surgery, metastatic colon cancer, multidisciplinary healthcare team

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Authors: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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Authors: F. Farzan Nasab, H. J. M. Geijselaers, I. Baran, A. De Boer

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A method is introduced for the coupled skin-rib optimization of a wing box where mass minimization is the objective and local buckling is the constraint. The structure is made of composite materials where continuity of plies in multiple adjacent panels (blending) has to be satisfied. Blending guarantees the manufacturability of the structure; however, it is a highly challenging constraint to treat and has been under debate in recent research in the same area. To fulfill design guidelines with respect to symmetry, balance, contiguity, disorientation and percentage rule of the layup, a reference for the stacking sequences (stacking sequence table or SST) is generated first. Then, an innovative fully gradient-based optimization approach in relation to a specific SST is introduced to obtain the optimum thickness distribution all over the structure while blending is fulfilled. The proposed optimization approach aims to turn the discrete optimization problem associated with the integer number of plies into a continuous one. As a result of a wing box deflection, a rib is subjected to load values which vary nonlinearly with the amount of deflection. The bending stiffness of a skin affects the wing box deflection and thus affects the load applied to a rib. This indicates the necessity of a coupled skin-rib optimization approach for a more realistic optimized design. The proposed method is examined with the optimization of the layup of a composite stiffened skin and rib of a wing torsion box subjected to in-plane normal and shear loads. Results show that the method can successfully prescribe a valid design with a significantly cheap computation cost.

Keywords: blending, buckling optimization, composite panels, wing torsion box

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Authors: Vijaya K. Srivastava, Davide Spinello

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This paper presents established 3ⁿ enumeration procedure for mixed integer optimization problems for solving multi-objective reliability and redundancy allocation problem subject to design constraints. The formulated problem is to find the optimum level of unit reliability and the number of units for each subsystem. A number of illustrative examples are provided and compared to indicate the application of the superiority of the proposed method.

Keywords: integer programming, mixed integer programming, multi-objective optimization, Reliability Redundancy Allocation

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Authors: Mitat Uysal, Aynur Uysal

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Artificial Intelligence (AI) is fundamentally driven by mathematics, with many of its core algorithms rooted in mathematical principles such as linear algebra, probability theory, calculus, and optimization techniques. This paper explores the deep connection between AI and mathematics, highlighting the role of mathematical concepts in key AI techniques like machine learning, neural networks, and optimization. To demonstrate this connection, a case study involving the implementation of a neural network using Python is presented. This practical example illustrates the essential role that mathematics plays in training a model and solving real-world problems.

Keywords: AI, mathematics, machine learning, optimization techniques, image processing

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Authors: Liudmila Garzanova, Lidia Ananyeva, Olga Koneva, Olga Ovsyannikova, Oxana Desinova, Mayya Starovoytova, Rushana Shayahmetova

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Objectives. Gastrointestinal involvement is one of the most common manifestations of systemic sclerosis (SSc). The aim of our study was to assess the frequency of gastrointestinal manifestations in SSc patients (pts) with interstitial lung disease (ILD) and their changes to rituximab (RTX) therapy. Methods. There were 103 pts with SSc in this study. The mean follow-up period was 12.6±10.7 months. The mean age was 47±12.9 years, females - 87 pts (84%), and the diffuse cutaneous subset of the disease 55 pts (53%). The mean disease duration was 6.2±5.5 years. All pts had ILD and were positive for ANA. 67% of them were positive for anti-topoisomerase-1. All patients received prednisolone at a dose of 11.3±4.5 mg/day, and immunosuppressants at inclusion received 47% of them. Pts received RTX due to the ineffectiveness of previous therapy for ILD. The cumulative mean dose of RTX was 1.7±0.6 grams. 90% of pts received omeprazole at a dose of 20-40 mg/day. Results. At inclusion, dysphagia was observed in 76 pts (74%), early satiety or vomiting in 32 pts (31%), and diarrhea in 20 pts (19%). We didn't observe any changes in gastrointestinal manifestation during RTX therapy. There was a decrease in the number of pts with dysphagia from 76 (74%) to 66 (64%), but it was insignificant. The number of pts with early satiety or vomiting and diarrhea didn't change. Conclusion. In our study, gastrointestinal involvement was observed in most of the pts with SSc-ILD. We didn't find any significant changes in gastrointestinal manifestations during RTX therapy. RXT does not worsen gastrointestinal manifestations in SSc-ILD.

Keywords: systemic sclerosis, dysphagia, rituximab, gastrointestinal manifestations

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Authors: Fariborz Ahmadi, Hamid Salehi, Khosrow Karimi

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A sensor network is set of sensor nodes that cooperate together to perform a predefined tasks. The important problem in this network is power consumption. So, in this paper one algorithm based on the eurygaster life is introduced to minimize power consumption by the nodes of these networks. In this method the search space of problem is divided into several partitions and each partition is investigated separately. The evaluation results show that our approach is more efficient in comparison to other evolutionary algorithm like genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, sensor network optimization

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Authors: Gaohuizi Guo, Ning Zhang

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Firefly algorithm (FA) and Sine Cosine algorithm (SCA) are two very popular and advanced metaheuristic algorithms. However, these algorithms applied to multi-objective optimization problems have some shortcomings, respectively, such as premature convergence and limited exploration capability. Combining the privileges of FA and SCA while avoiding their deficiencies may improve the accuracy and efficiency of the algorithm. This paper proposes a hybridization of FA and SCA algorithms, named multi-objective firefly-sine cosine algorithm (MFA-SCA), to develop a more efficient meta-heuristic algorithm than FA and SCA.

Keywords: firefly algorithm, hybrid algorithm, multi-objective optimization, sine cosine algorithm

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Authors: Broderick Crawford, Ricardo Soto, Natalia Berrios, Eduardo Olguin

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In this paper, we present a binary cat swarm optimization for solving the Set covering problem. The set covering problem is a well-known NP-hard problem with many practical applications, including those involving scheduling, production planning and location problems. Binary cat swarm optimization is a recent swarm metaheuristic technique based on the behavior of discrete cats. Domestic cats show the ability to hunt and are curious about moving objects. The cats have two modes of behavior: seeking mode and tracing mode. We illustrate this approach with 65 instances of the problem from the OR-Library. Moreover, we solve this problem with 40 new binarization techniques and we select the technical with the best results obtained. Finally, we make a comparison between results obtained in previous studies and the new binarization technique, that is, with roulette wheel as transfer function and V3 as discretization technique.

Keywords: binary cat swarm optimization, binarization methods, metaheuristic, set covering problem

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Authors: Mohammad Y. Badiee, Saeed Golestani, Mir Saman Pishvaee

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In recent years consumers and governments have been pushing companies to design their activities in such a way as to reduce negative environmental impacts by producing renewable product or threat free disposal policy more and more. It is therefore important to focus more accurate to the optimization of various aspect of total supply chain. Modeling a supply chain can be a challenging process due to the fact that there are a large number of factors that need to be considered in the model. The use of multi-objective optimization can lead to overcome those problems since more information is used when designing the model. Uncertainty is inevitable in real world. Considering uncertainty on parameters in addition to use multi-objectives are ways to give more flexibility to the decision making process since the process can take into account much more constraints and requirements. In this paper we demonstrate a stochastic scenario based robust model to cope with uncertainty in a closed-loop multi-objective supply chain. By applying the proposed model in a real world case, the power of proposed model in handling data uncertainty is shown.

Keywords: supply chain management, closed-loop supply chain, multi-objective optimization, goal programming, uncertainty, robust optimization

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Authors: Eunhwa Jun

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This case report describes the misdiagnosis of a patient who presented with right arm pain as cervical disc herniation. The patient had several underlying conditions, including hypertension, diabetes mellitus, liver cirrhosis, a history of lung cancer with left lower lobe lobectomy, and adjuvant chemoradiotherapy. An external cervical spine MRI revealed central protruding discs at the C4-5-6-7 levels. Despite treatment with medication and epidural blocks, the patient's pain persisted. A C-RACZ procedure was planned, but the patient's pain had worsened before admission. Using ultrasound, a brachial plexus block was attempted, but the brachial plexus eluded clear visualization, hinting at underlying neurological complexities. Chest CT revealed a new, large soft tissue mass in the right supraclavicular region with adjacent right axillary lymphadenopathy, leading to the diagnosis of metastatic squamous cell carcinoma. Palliative radiation therapy and chemotherapy were initiated as part of the treatment plan, and the patient's pain score decreased to 3 out of 10 on the Numeric Rating Scale (NRS), revealing the pain was due to metastatic lung cancer.

Keywords: supraclavicula brachial plexus metastasis, cervical disc herniation, brachial plexus block, metastatic lung cancer

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Authors: Areej Makeineldein Mustafa

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The study evaluates the management processes and healthcare provider compliance with the National Institute for Health and Care Excellence recommendations for constipation management. We aimed to evaluate the adherence to National Institute for Health and Care Excellence guidelines in the management of constipation during the period from February to June 2023. We collected data from a random sample ( 51 patients) over 4 months with inclusion criteria for patients above 60 who were just admitted to the care of the elderly department during this period. Patient age, sex, medical records for constipation, acute or chronic constipation, or opioid-induced constipation, and treatment options were used to identify constipation and the type of treatment given. Our findings indicate that there is a gap between practice and National Institute for Health and Care Excellence guideline steps; only 3 patient was given medications according to National Institute for Health and Care Excellence guidelines in order of combination or steps of escalation. Addressing these gaps could potentially lead to enhanced patient outcomes and an overall improvement in the quality of care provided to individuals suffering from constipation.

Keywords: constipation, elderly, management, patient

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Authors: Catharina Lindberg, Cecilia Fagerstrom, Ania Willman

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Patients in high-tech care environments are usually dependent on both formal/informal caregivers and technology, highlighting their vulnerability and challenging their autonomy. Autonomy presumes that a person has education, experience, self-discipline and decision-making capacity. Reference to autonomy in relation to patients in high-tech care environments could, therefore, be considered paradoxical, as in most cases these persons have impaired physical and/or metacognitive capacity. Therefore, to understand the prerequisites for patients to experience autonomy in high-tech care environments and to support them, there is a need to enhance knowledge and understanding of the concept of patient autonomy in this care context. The development of concepts and theories in a practice discipline such as nursing helps to improve both nursing care and nursing education. Theoretical development is important when clarifying a discipline, hence, a theoretical framework could be of use to nurses in high-tech care environments to support and defend the patient’s autonomy. A meta-synthesis was performed with the intention to be interpretative and not aggregative in nature. An amalgamation was made of the results from three previous studies, carried out by members of the same research group, focusing on the phenomenon of patient autonomy from a patient perspective within a caring context. Three basic approaches to theory development: derivation, synthesis, and analysis provided an operational structure that permitted the researchers to move back and forth between these approaches during their work in developing a theoretical framework. The results from the synthesis delineated that patient autonomy in a high-tech care context is: To be in control though trust, co-determination, and transition in everyday life. The theoretical framework contains several components creating the prerequisites for patient autonomy. Assumptions and propositional statements that guide theory development was also outlined, as were guiding principles for use in day-to-day nursing care. Four strategies used by patients to remain or obtain patient autonomy in high-tech care environments were revealed: the strategy of control, the strategy of partnership, the strategy of trust, and the strategy of transition. This study suggests an extended knowledge base founded on theoretical reasoning about patient autonomy, providing an understanding of the strategies used by patients to achieve autonomy in the role of patient, in high-tech care environments. When possessing knowledge about the patient perspective of autonomy, the nurse/carer can avoid adopting a paternalistic or maternalistic approach. Instead, the patient can be considered to be a partner in care, allowing care to be provided that supports him/her in remaining/becoming an autonomous person in the role of patient.

Keywords: autonomy, caring, concept development, high-tech care, theory development

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Authors: Xiang Li, Jian-Qiao Sun

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As the crucial component of city traffic network, intersections have significant impacts on urban traffic performance. Despite of the rapid development in transportation systems, increasing traffic volumes result in severe congestions especially at intersections in urban areas. Effective regulation of vehicle flows at intersections has always been an important issue in the traffic control system. This study presents a multi-objective optimization method at intersections with cellular automata to achieve better traffic performance. Vehicle conflicts and pedestrian interference are considered. Three categories of the traffic performance are studied including transportation efficiency, energy consumption and road safety. The left-turn signal type, signal timing and lane assignment are optimized for different traffic flows. The multi-objective optimization problem is solved with the cell mapping method. The optimization results show the conflicting nature of different traffic performance. The influence of different traffic variables on the intersection performance is investigated. It is observed that the proposed optimization method is effective in regulating the traffic at the intersection to meet multiple objectives. Transportation efficiency can be usually improved by the permissive left-turn signal, which sacrifices safety. Right-turn traffic suffers significantly when the right-turn lanes are shared with the through vehicles. The effect of vehicle flow on the intersection performance is significant. The display pattern of the optimization results can be changed remarkably by the traffic volume variation. Pedestrians have strong interference with the traffic system.

Keywords: cellular automata, intersection, multi-objective optimization, traffic system

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Authors: Azza T. Tahera, Eman M. Ahmeda, Nadia A. Khalila, Yassin M. Nissanb

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New 3-(pyridin-4-yl)-[1,2,4] triazolo [4,3-b] pyridazine derivatives 2a-i, 4a,b and 6a,b were designed, synthesized and evaluated as cytotoxic agents. All compounds were investigated for their in vitro cytotoxicity at a single dose 10-5M concentration towards 60 cancer cell lines according to USA NCI protocol. The preliminary screening results showed that the majority of tested compounds exhibited remarkable activity against SR (leukemia) cell panel. Molecular docking for all synthesized compounds was performed on the active site of c-Met kinase. The most active compounds, 2f and 4a were further evaluated at a seven dose level screening and their IC50 as a c-Met kinase inhibitors were determined in vitro.

Keywords: triazolopyridazines, pyridazines, cytotoxic activity, cell panel

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Authors: Dana Mohammed, Fatemah Abdullah, Hawraa Ali, Najat Al-Shaer, Rawan Al-Awadhi, , Magdy Helal

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We study the patient service performance at the emergency department of a major Kuwaiti public hospital, using discrete simulation and lean concepts. In addition to the common problems in such health care systems (over crowdedness, facilities planning and usage, scheduling and staffing, capacity planning) the emergency department suffered from several cultural and patient behavioural issues. Those contributed significantly to the system problems and constituted major obstacles in maintaining the performance in control. This led to overly long waiting times and the potential of delaying providing help to critical cases. We utilized the visual management tools to mitigate the impact of the patients’ behaviours and attitudes and improve the logistics inside the system. In addition a proposal is made to automate the date collection and communication within the department using RFID-based barcoding system. Discrete event simulation models were developed as decision support systems; to study the operational problems and assess achieved improvements. The simulation analysis resulted in cutting the patient delays to about 35% of their current values by reallocating and rescheduling the medical staff. Combined with the application of the visual management concepts, this provided the basis to improving patient service without any major investments.

Keywords: simulation, visual management, health care system, patient

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Authors: Nashalla Gwyn Nyinda

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The ancient system of Tibetan Medicine, known as Sowa Rigpa across the Himalayan regions, is a systematic system of healing encouraging balance primarily through diet and behavior modifications. With the rise of the popularity of Tibetan Medicine, compliance is critical to successful treatment outcomes. As patients learn more about who they are as individuals and how their elemental balances or imbalances affect disorders and mental-emotional balance, they develop faith and dedication to their healing process. Specifically, regarding diet and behavior and the basic principles of the medical system, patient compliance increases dramatically in all treatment areas when they understand why a treatment or dietary prescription guidance is effective. Successful responses to Tibetan treatment rely on a buy-in from the patient. Trust between the slower process of Traditional medicine treatments, the Tibetan physician and the patient is a cornerstone of treatment. The resulting decrease in the use of allopathic medicine and better health outcomes for acute and chronic disorders are well documented. This paper addresses essential points of the Tibetan Medicine system, dialogue between doctor and patient focused on appropriate and seasonal changing dietetics. Such fluctuating treatment approaches, based on external elemental factors, dramatically increase treatment outcomes. Specifically, this work addresses why allopathic medicine models may need more trust development between practitioner and patient.

Keywords: compliancy in treatment, diet and lifestyle medicine, nature and elements as medicine, seasonal diets, Sowa Rigpa, traditional Tibetan medicine, treatment outcomes

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Authors: Hichem Kmimech, Achref Jabeur Telmoudi, Lotfi Nabli

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The estimation of the initial marking minimum (MIM) is a crucial problem in labeled Petri nets. In the case of multiple choices, the search for the initial marking leads to a problem of optimization of the minimum allocation of resources with two constraints. The first concerns the firing sequence that could be legal on the initial marking with respect to the firing vector. The second deals with the total number of tokens that can be minimal. In this article, the MIM problem is solved by the meta-heuristic particle swarm optimization (PSO). The proposed approach presents the advantages of PSO to satisfy the two previous constraints and find all possible combinations of minimum initial marking with the best computing time. This method, more efficient than conventional ones, has an excellent impact on the resolution of the MIM problem. We prove through a set of definitions, lemmas, and examples, the effectiveness of our approach.

Keywords: marking, production system, labeled Petri nets, particle swarm optimization

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Authors: Stephanie Yun Yu Law

Abstract:

Background: This study aims to investigate into communication between trainee doctors and patients, especially how doctor’s reaction to patient’s emotional issues expressed in the consultation affect patient’s satisfaction. Objectives: Thus, there are three aims in this study, 1.) how do trainee doctors react to patients emotional cues in OSCE station? 2.) Any differences in the respond type to emotional cues between first year students and third year students? 3.) Is response type (reducing space) related to OSCE outcome (patient satisfaction and expert rating)? Methods: Fifteen OSCE stations was videotaped, in which 9 were stations with first-year students and 6 were with third-year students. OSCE outcomes were measured by Communication Assessment Tool and Examiners Checklist. Analyses: All patient’s cues/concerns and student’s reaction were coded by Verona Coding Definitions of Emotional Sequence. Descriptive data was gathered from Observer XT and logistic regression (two-level) was carried out to see if occurrence of reducing space response can be predicted by OSCE outcomes. Results: Reducing space responses from all students were slightly less than a half in total responses to patient’s cues. The mean percentage of reducing space behaviours was lower among first year students when compared to third year students. Patient’s satisfaction significantly (p<0.05) and negatively predicted reducing space behaviours. Conclusions: Most of the medical students, to some extent, did not provide adequate responses for patient’s emotional cues. But first year students did provide more space for patients to talk about their emotional issues when compared to third year students. Lastly, patients would feel less satisfied if trainee doctors use more reducing space responses in reaction to patient’s expressed emotional cues/concerns. Practical implications: Firstly, medical training programme can be tailored on teaching students how to detect and respond appropriately to emotional cues in order to improve underperformed student’s communication skills in healthcare setting. Furthermore, trainee doctor’s relationship with patients in clinical practice can also be improved by reacting appropriately to patient’s emotive cues in consultations (such as limit the use of reducing space behaviours).

Keywords: doctors-patients communication, applied clinical psychology, health psychology, healthcare professionals

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